A Decision Model for Strategic Evaluation of Enterprise Information Technologies

Enterprise information technologies (EITs), which are strategic systems seeking to integrate the processes and databases of the entire organization and beyond, require a significant investment of money and human resources in return for the promise of a global business model and its associated far-reaching benefits. Their evaluation/justification must be completed with organizational goals and requirements included in the decision, or the organization could lose financially and competitively. Besides traditional financial models, e.g., ROI (return on investment), that are primarily meant for short-term financial justification purposes, there is a paucity of methods for the evaluation of the strategic and intangible costs and benefits that EITs afford organizations as a whole. This article introduces the use of a robust quantitative technique called the analytical hierarchy process (AHP) that can integrate a diverse range of factors (strategic and operational, and tangible and intangible) into one model. the approach can be easily understood by managers and analysts and has a history of application to other types of strategic justification decisions.     

Pattern discovery of fuzzy time series for financial prediction

A fuzzy time series data representation method based on the Japanese candlestick theory is proposed and used in assisting financial prediction. The Japanese candlestick theory is an empirical model of investment decision. The theory assumes that the candlestick patterns reflect the psychology of the market, and the investors can make their investment decision based on the identified candlestick patterns. We model the imprecise and vague candlestick patterns with fuzzy linguistic variables and transfer the financial time series data to fuzzy candlestick patterns for pattern recognition. A fuzzy candlestick pattern can bridge the gap between the investors and the system designer because it is visual, computable, and modifiable. The investors are not only able to understand the prediction process, but also to improve the efficiency of prediction results. The proposed approach is applied to financial time series forecasting problem for demonstration. By the prototype system which has been established, the investment expertise can be stored in the knowledge base, and the fuzzy candlestick pattern can also be identified automatically from a large amount of the financial trading data.     

非结构化智能金融投研平台的开发与行业应用

当前针对非结构化数据处理的研究多集中于实验态的技术实现,对于其在金融投研业务中落地应用的整体架构与路径的研讨则较为缺乏.为此,提出将大数据、自然语言处理、知识图谱等技术结合起来进行智能化投研平台的研发设计,并实现其在真实金融投研场景的应用.该平台基于Hadoop分布式系统进行数据采集、存储与计算,集成了传统文本处理技术...     

Return on Infrastructure, the New ROI

IT executives frequently must be able to communicate IT's value in real economic terms, characterizing how technology infrastructure financially benefits the business relative to the company's financial performance objectives. Traditionally, the approach taken has focused on the capital investment process, with return on investment being the primary metric. However, ROI approaches identify financial results pertaining to a specific project, rather than IT programs as a whole, and can be misleading. A new financial metric, return on infrastructure employed (ROIE), has economic and real practical meaning to senior executive management because it recognizes IT as both an asset and a service. ROIE is a new financial management tool with which to judge the business contribution of IT as a whole; using it can motivate management behaviors and disciplines that are essential for success in the modern-day information economy.     

A decision support system for evaluating intangible investments

In this research project we have connected the procedural and substantive decision support by means of modern information technology. We have showed how the semistructured strategic decisions concerning intangible investments can be supported effectively by relating appropriate analysis methods to the different phases of the investment process. Because for the intangible investments there is no well-defined solution procedure available, a variety of methods must be integrated to support the solution process.

As a demonstrative example we showed how the intangible investments in logistic systems can be managed. It was highlighted that the logistics systems are complex, cross-functional systems that affect all major functions or departments within the firm beginning from the raw material deliveries and ending with the deliveries of finished goods. Investments in the logistics systems have corporatewide, cross-functional effects, and the investment decisions are strategic decisions. Consequently, the investments in the logistics systems should be strategically justified, not only cost-justified. The cross-functional effects imply that the investment analysis concerning the whole logistics system must be fulfilled under multiple, diversified criteria. We can not, however, ignore the financial, cost and revenue oriented, traditional investment criteria. They just have to be used in a new, flexible way in relation to the goals and objectives of the firm.

Strategic planning is a managerial area where semistructured problems frequently exist. One of the key problems faced in strategic management is the issue of investment decisions. Investments in information systems, logistic systems, flexible production systems, corporate image, etc, are examples of complex investment problems that are difficult to quantify and analyze with traditional techniques. Modern computer technology can enrich the analysis and improve the quality of strategic decision making.     

Automated Compliance Checking Methodology for Non-Log Operations

ABSTRACT

Compliance Management (CM) is the management process that an organization implements to ensure organizational compliance with relevant requirements and expectations. The most complicated, time-consuming, and costly process in CM is compliance checking because it requires a person who has a good knowledge in policy to examine whether the current operations meet the policy requirements. Many researchers have tried to study better ways to automate the compliance checking process, but most of them require the operation logs in to the computer systems. This paper proposes a methodology to enable the automation of compliance checking for those operations that have no log in computer systems by using questions and answers principle to cooperate with the semantic web technologies. Since there are some operations that cannot be understood by computer systems, using questions is one way to gather the answers, such as operation log to evaluate their compliance. The proposed methodology can help noncertified auditors perform the compliance checking so that the time and cost of compliance checking would be greatly reduced.     

The Place of TRIZ in a Holistic Design Methodology

Design is key to a project’s profitability and therefore increased PROFIT by DESIGN is the goal of improvements to the design process. Business requirements can be summarised as Better, Faster, Cheaper and considerable investment has been made in technology and methods for the design process to enable this. There is evidence to suggest that these investments have resulted in products themselves getting better but not necessarily produced faster or cheaper. A model of the design process has been developed which makes explicit its key elements. The six key elements or dimensions of the design process are: Analyse; Understand; Decide; Create; Capture; and Know. Investments in design technology may not be reaching their full potential due to a mismatch between the relative importance of the attributes of a good designer and the areas where investments have been made, leading to a potential loss of balance in the design process. This is compounded by failure to take a holistic view of changes to the process including mitigation of any downside. In particular the Create dimension, which is seen as the most important attribute of a good designer, has had the least investment and also is the most vulnerable because it is optional. In recognition of this fact, Rolls‐Royce is using the TRIZ methodology to provide designers with an improved capability. However it also is recognised that providing capability alone is not enough. The right motivation and opportunity are also needed, and this requires the appropriate organisational and cultural features to be in place. What is needed is a people centred process that is business driven and product focused.     

Semantic model for knowledge representation in e-business

Semantic knowledge representation is the key for the development of present intelligent systems. Furthermore, the Semantic Web provide a formal representation and knowledge-driven set of technologies to enable automation of business processes. Despite the new trends on business process automation based on semantic technologies and Web Services, a number of business processes still require human intervention. In this paper we address the problem of ontology-based process representation based on expert’s knowledge, considering both tasks executed by means of web services and tasks executed by persons. In this way, fully-automated and semi-automated processes (guided by a person) could be represented and executed. The proposed model is based on the set of situations that can be identified by an expert in a given process and the actions required in each situation. For validating our approach, a sales supporting system based on the proposed architecture has been developed. The proof-of concept system has been running for a remarkably time, supporting the sales process for non-expert sellers.     

Robo-advisors and investment intention: A perspective of value-based adoption

Financial robo-advisors have been widely used to assist individuals in their investment decisions, making it important to reduce uncertainties in the assistance process. Existing empirical studies rarely explore uncertainty reduction strategies and their implications on users’ investment intentions in the context of financial robo-advisors; our study attempts to address this gap. We construct a model to explain how uncertainty reduction strategies affect users’ investment intention in using financial robo-advisors. By collecting and analyzing a sample of 307 financial robo-advisor users, we find that algorithmic interpretability, structural assurance, and interactivity as uncertainty reduction strategies are positively related to users’ investment intention through the value-based adoption mechanism. Our research extends the value-based adoption model and uncertainty reduction theory in the financial robo-advisor context. We provide insights to financial robo-advisor service providers about focusing on improving algorithmic transparency, third-party assurance, and interactivity of financial robo-advisors to enhance perceived value and investment intention.     

A cost/benefit model for investments in inventory and preventive maintenance in an imperfect production system

In this research, a cost/benefit model is developed for supporting investment strategies about inventory and preventive maintenance in an imperfect production system. The effect of such investments on the return is expressed as a function of measurable variables. Using this model, the decision maker can decide whether investments in inventory and preventive maintenance are necessary and how much to invest. This investment model is developed for an imperfect production system with imperfect product quality and supplied quantity. Investments in inventory and preventive maintenance increase service level for the customer and reduce the proportion of defective products, and hence affect stockout and backlog of supplied products and the delivery time to the customer. This model includes in its scope investment in inventory and preventive maintenance, manufacturing cost, inventory cost, backlog cost, stockout cost, and delay cost. This model can be used to evaluate the effects of investments on the financial cost/benefit and other relevant critical performance measures. This model can be solved by an iterative process using the Sequential Quadratic Programming Method. The optimal investment in inventory with respect to the service level and the optimal investment in preventive maintenance with respect to the proportion of defective items can be obtained first, and then other relevant costs can also be obtained.     

Test-Driven Development for Spreadsheet Risk Management

Spreadsheet technology is central to the functioning of the financial sector, but professionally created spreadsheets have a high level of error, which highlights the need for innovative supporting processes and tools. The current global financial crisis will likely accelerate this need because anticipated regulation will require novel, innovative risk management methods and technologies that cover development, risk assessment, review, and other spreadsheet activities. These methods will need to be easy to understand and use and will have to serve multiple stakeholders' needs. Test-driven spreadsheet development (TDSD) is one such method. TDSD provides an ideal fit with existing market-leading spreadsheet management processes and can assist managers and auditors in the assessment and control of spreadsheet risk.     

R&D Investment Enhance the Financial Performance of Company Driven by Big Data Computing and Analysis

The application of computer technology, especially the emergence of some statistical software and graphic presentation technology, has enabled many areas of research that require a large amount of data analysis. This paper discusses the relationship between R&D investment and corporate financial performance, and further studies the effect of environmental regulations on this relationship through these technologies. The unbalanced panel data of listed companies from 2007 to 2016 were used as a sample, and then corresponding regression modelswere established through logical reasoning. Empirical analysis has found that there is an inverted U-shaped relationship between R&D investment and company financial performance, and there is a U-shaped relationship between the intensity of environmental regulations and companies’ investment in R&D. Another finding is that the inverted U-shaped relationship between companies’ R&D investment and financial performance is moderated by environmental regulations in such a way that greater environmental regulations is associated with a lower point of maximum efficiency in the inverted U-shaped curve. This indicates that the strengthening of environmental regulations will affect a company’s resource allocation, which will lead to a reduced investment in production, R&D and so on, thus reducing the peak value of financial performance.     

Image-Based Network Rendering of Large Meshes for Cloud Computing

Recent advances in sensing and software technologies enable us to obtain large-scale, yet fine 3D mesh models of cultural assets. However, such large models cannot be displayed interactively on consumer computers because of the performance limitation of the hardware. Cloud computing technology is a solution that can process a very large amount of information without adding to each client user’s processing cost. In this paper, we propose an interactive rendering system for large 3D mesh models, stored on a remote environment through a network of relatively small capacity machines, based on the cloud computing concept. Our system uses both model- and image-based rendering methods for efficient load balance between a server and clients. On the server, the 3D models are rendered by the model-based method using a hierarchical data structure with Level of Detail (LOD). On the client, an arbitrary view is constructed by using a novel image-based method, referred to as the Grid-Lumigraph, which blends colors from sampling images received from the server. The resulting rendering system can efficiently render any image in real time. We implemented the system and evaluated the rendering and data transferring performance.     

Difficulties in Quantifying Financial Losses that Could Be Reduced by Ergonomic Solutions

There is currently a significant amount of discussion regarding new ways to insert ergonomics into the business community through adding financial benefits; however, analysis must be performed to justify this type of investment. Occupational problems that could be reduced by ergonomics solutions can be expressed as financial losses. Although the impact and importance of these losses are high, the difficulties in their quantification prevent adequate cost‐benefit analysis. This article aims to document evidence of the difficulties encountered when quantifying the financial losses that are caused by problems that could be reduced by ergonomic solutions. In this study, we performed a literature review concerning the financial costs related to occupational problems from the perspective of ergonomics. The results indicate that losses that occur mainly concern the productivity of the working process or the workers. The chief barriers documented in the scientific literature are the information cost, the multifactorial nature of the problem, the absence of information, and the methods of measurement. © 2012 Wiley Periodicals, Inc.     

Application of improved clustering algorithm in investment recommendation in embedded system

The user's investment behaviour is individual, and group-oriented, which can reflect the user's cognitive background and interest on a certain extent. The user investment group can help users to find similar investment partners. Users can view the investment or other related people's interests. With the development of the Internet financial industry, people's demand for Internet financial knowledge services has become increasingly strong. Accessing financial information and conducting financial transactions through online financial platforms has become normal for investors. As a popular research area, the recommendation system can help users to better use Internet information, improve user loyalty, and promote products. In this paper, an improved kernel cluster-based incremental clustering method is proposed, and the stock information of the Shanghai Stock Exchange is used as the experimental data for cluster mining. The experimental results show that the improved kernel-based incremental clustering algorithm proposed in this paper can complete the investment recommendation for financial users. For a certain extent, it reduces the risk of financial investment, enhances the stability of the financial market, and has a strong positive effect.     

A hybrid knowledge-sharing model for corporate foreign investment in China’s construction market

The research proposes a hybrid knowledge-sharing model, which integrates the concepts of the self-organizing feature map optimization, fuzzy logic control, and hyper-rectangular composite neural networks, to provide 32 rules that suggest performing or not performing foreign construction investment. The database is derived from 520 quarterly financial reports of all listed construction companies in Taiwan that have now or in the past five years made foreign investment in China’s construction industry. The input variables are set to all 25 financial ratios assessable in public, reducing to 11 ratios after feature deduction using t-test. The model yields a high successful classification rate of 90.6% and generates 14 and 18 rules for Taiwan construction companies performing or not performing foreign investment in China, respectively. The valuable rules give user a closer look at what is the appropriate corporate financial status, what knowledge can be shared from the interpretations of the rules, and the impact by investment on corporate finance.     

An empirical study of design-of-experiment data mining for yield-loss diagnosis for semiconductor manufacturing

To maintain competitive advantages, semiconductor industry has strived for continuous technology migrations and quick response to yield excursion. As wafer fabrication has been increasingly complicated in nano technologies, many factors including recipe, process, tool, and chamber with the multicollinearity affect the yield that are hard to detect and interpret. Although design of experiment (DOE) is a cost effective approach to consider multiple factors simultaneously, it is difficult to follow the design to conduct experiments in real settings. Alternatively, data mining has been widely applied to extract potential useful patterns for manufacturing intelligence. However, because hundreds of factors must be considered simultaneously to accurately characterize the yield performance of newly released technology and tools for diagnosis, data mining requires tremendous time for analysis and often generates too many patterns that are hard to be interpreted by domain experts. To address the needs in real settings, this study aims to develop a retrospective DOE data mining that matches potential designs with a huge amount of data automatically collected in semiconductor manufacturing to enable effective and meaningful knowledge extraction from the data. DOE can detect high-order interactions and show how interconnected factors respond to a wide range of values. To validate the proposed approach, an empirical study was conducted in a semiconductor manufacturing company in Taiwan and the results demonstrated its practical viability.     

PoE和NVR技术在财务监控系统中的应用

财务部门现有的监控系统采用数字模拟监技术,增加监控点难度大;监控数据备份通用性差,且无法远程查看;特别是在断电时无法持续工作,监控有时间上的盲区.针对该系统以上缺陷,本文将采用PoE、UPS、无线、NVR等技术改造原有监控系统,以满足需求.     

Key technologies for safe and autonomous drones

Drones/UAVs are able to perform air operations that are very difficult to be performed by manned aircrafts. In addition, drones’ usage brings significant economic savings and environmental benefits, while reducing risks to human life. In this paper, we present key technologies that enable development of drone systems. The technologies are identified based on the usages of drones (driven by COMP4DRONES project use cases). These technologies are grouped into four categories: U-space capabilities, system functions, payloads, and tools. Also, we present the contributions of the COMP4DRONES project to improve existing technologies. These contributions aim to ease drones’ customization, and enable their safe operation.